Gaussian grids in R

Hi Matt,

The crux here is to find the pro4 string associated with your projection. 
After finding that, you can use spTransform to reproject the data. However, 
after reprojection the T62 grid is not a grid any more. You already observed 
this, your pixelsize changes with latitude. This means that you have to 
perform some kind of interpolation, warping or resampling.

One option to find the proj4 string is to post a question on the proj4 list 
[1]. The response on this is often quite good and fast.

Best,
Paul

[1] http://lists.maptools.org/mailman/listinfo/proj

On 07/11/2010 05:45 AM, Matthew Landis wrote:

Edzer - I'm using the T62 grids of temperature and precip to feed a model. 
The other datasets in the workflow are in geographic CRS, so I need to 
reproject the T62 data into geographic coordinates as well.

Since the T62 grid is nearly regular except with small variations towards 
the poles, my current strategy is to ignore the changes in cell size and 
pretend the grid is actually regular with a cell size corresponding to that 
of the lower latitudes.  I just thought it would be more satisfying to be 
able to specify the CRS more precisely.

Best,
Matt

On 7/10/2010 2:22 PM, Edzer Pebesma wrote:

Matt, why exactly would you want to coerce these data into a regular grid?

On 07/01/2010 04:05 PM, Matthew Landis wrote:

Dear  R-sig-geo members,

I wonder if any of you have suggestions about how to import and use
rasters with a spectral Gaussian T62 CRS in R.  I'm not very familiar
with this coordinate system (commonly used for climate models), and I
haven't been able to discover tools for dealing with them in R, either
in PROJ.4 or mapproj or anywhere else, despite extensive scouring of the
web.  Details of Gaussian grids can be seen at
http://en.wikipedia.org/wiki/Gaussian_grid and
http://www.nco.ncep.noaa.gov/pmb/docs/on388/tableb.html#GRID98

Specifically, I'm trying to use output from the NCEP CFS climate models
(see http://cfs.ncep.noaa.gov/cfs/monthly/tmp2m/ -- these are in GRIB
format).  A different example of a T62 grid can be downloaded in netCDF
format at http://www.sage.wisc.edu/iamdata/grid.php.
The goal is to transform the CRS into geographic lat/lon coordinates to
be more compatible with our other datasets.  The big problem with
getting these data into a SpatialGrid or SpatialPixelsDataFrame is that
the latitude cells are not equally spaced - they get smaller towards the
poles.  I may be able to approximate it to a regular grid by ignoring
the changes to the poles (they are rather small after all), but I'd
rather do it properly if possible.

Code below shows extracting latitudes from a T62 grid and plotting the
changes in cell size with latitude.

library('ncdf')
library('sp')
nc<- 'C:/scratch/cfs/pop_den_1995_T62.nc' # Downloaded  from
http://www.sage.wisc.edu/iamdata/grid.php

# Open the file and get latitude and longitude
nc<- open.ncdf(ncfile)
lat<- get.var.ncdf(nc, varid = 'latitude')
lon<- get.var.ncdf(nc, varid = 'longitude')
close.ncdf(nc)

# Generate coordinates for each grid cell
x<- rep(lon, length(lat))
y<- rep(lat, each = length(lon))
sp<- SpatialPoints(cbind(x,y))
# temp<- SpatialPixels(points = sp) # Doesn't work.  points have to be
regular grid

# Show how the cell size changes with latitude
cell.size<- diff(rev(lat))
plot(lat[-1], cell.size)

Many thanks for any suggestions!

Matt